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This study assessed the effectiveness of a fully automated surveillance system for the detection of healthcare-associated infections (HCAIs) in intensive care units. Manual ward surveillance (MS) and electronic surveillance (ES) were performed for two intensive care units of the Vienna General Hospital. All patients admitted for a period longer than 48 h between 13 November 2006 and 7 February 2007 were evaluated according to HELICS-defined rules for HCAI. The sensitivity [...]

To provide a set of high-quality time-series physiologic and event data from anesthetic cases formatted in an easy-to-use structure.

(1) To evaluate a state-of-the-art natural language processing (NLP)-based approach to automatically de-identify a large set of diverse clinical notes. (2) To measure the impact of de-identification on the performance of information extraction algorithms on the de-identified documents.

Secondary use of clinical text is impeded by a lack of highly effective, low-cost de-identification methods. Both, manual and automated methods for removing protected health information, are known to leave behind residual identifiers. The authors propose a novel approach for addressing the residual identifier problem based on the theory of Hiding In Plain Sight (HIPS).

To assess the effect of a clinical decision support system (CDSS) integrated into an electronic health record (EHR) on antibiotic prescribing for acute respiratory infections (ARIs) in primary care.

To evaluate systems for estimating and preventing wrong-patient electronic orders in computerized physician order entry systems with a two-phase study.

Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) [...]

We explore relationships between health information seeking activities and engagement with healthcare professionals via a privacy-sensitive analysis of geo-tagged data from mobile devices.

To provide a legal and ethical analysis of some of the implementation challenges faced by the Population Therapeutics Research Group (PTRG) at Memorial University (Canada), in using genealogical information offered by individuals for its genetics research database.

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic [...]